By Theodore Tsekeris, Loukas Dimitriou, Antony Stathopoulos (auth.), Andreas Fink, Franz Rothlauf (eds.)
The e-book to hand offers a cautious choice of appropriate functions of CI tools for shipping, logistics, and provide chain administration difficulties. The chapters illustrate the present cutting-edge within the software of CI tools in those fields and may aid and encourage researchers and practitioners to use and improve effective tools. a couple of contributions during this ebook are prolonged models of papers awarded at EvoTransLog2007: the 1st eu Workshop on Evolutionary Computation in Transportation and Logistics which was once held in Valencia, Spain, in 2007. nearly all of contributions are from extra, in particular chosen researchers, who've performed appropriate paintings in numerous components of delivery, logistics, and provide chain administration. The aim is to generally conceal consultant purposes in those fields in addition to forms of resolution ways. at the software facet, the contributions specialise in layout of site visitors and transportation networks, motor vehicle routing, and different very important facets of provide chain administration resembling stock administration, lot sizing, and lot scheduling. at the process aspect, the contributions care for evolutionary algorithms, neighborhood seek ways, and scatter seek mixed with different CI ideas resembling neural networks or fuzzy techniques. The publication is based in keeping with the applying domain names. therefore, it has 3 elements facing site visitors and transportation networks, car routing, and provide chain management.
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Extra info for Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management
A conceptual framework for optimal transportation systems planning with integrated supply and demand models. Transportation Science 20, 37–47 (1986) 15. : Transportation network equilibrium, design and aggregation: Key developments and research opportunities. Transport Reviews 18, 257–278 (1985) 16. : A simulated annealing approach to the network design problem with variational inequality constraints. Transportation Science 26, 18–26 (1992) 17. : An overview of nontraditional formulations of static and dynamic equilibrium network design.
All these approaches employ static assignment procedures to calculate the traﬃc ﬂows after having improved the network. Furthermore, models for traﬃc ﬂow estimation at dynamic disequilibrium states  and dynamic equilibrium algorithms  have been proposed and tested. A few models have also been considered for treating the uncertainty in various system attributes, such as the demand  and travel time . In addition, the C-NDP with travel time reliability requirements has been studied in  by the use of approximation methods in order to estimate the statistical properties of the system attributes and, especially, the Probability Density Function (PDF) of the T T T , which ends up with solving a sequential quadratic programming problem.
Equilibrium decomposed optimization: A heuristic for the continuous equilibrium network design problem. Transportation Science 21, 254–263 (1987) 36. : Robust transportation network design under demand uncertainty. Computer-Aided Civic Infrastructure Engineering 22, 6–18 (2007) 37. : Stochastic dynamic network design problem. Transportation Research Record 1771, 106–113 (2001) 38. : A capacity paradox in network design and how to avoid it. Transportation Research, Part A: Policy and Practice 32, 539–545 (1998) 39.
Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management by Theodore Tsekeris, Loukas Dimitriou, Antony Stathopoulos (auth.), Andreas Fink, Franz Rothlauf (eds.)